• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.1
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• pp.43-52
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• 2013

Pervasive computing and social network are good resources in recommendation method. Collaborative filtering is one of the most popular recommendation methods, but it has some limitations such as rating sparsity. Moreover, it does not consider social network in pervasive computing environment. We propose an effective proactive friend recommendation method using social network and contexts in pervasive computing environment. In collaborative filtering method, users need to rate sufficient number of items. However, many users don't rate items sufficiently, because the rating information must be manually input into system. We solve the rating sparsity problem in the collaboration filtering method by using contexts. Our method considers both a static and a dynamic friendship using contexts and social network. It makes more effective recommendation. This paper describes a new friend recommendation method and then presents a music friend scenario. Our work will help e-commerce recommendation system using collaborative filtering and friend recommendation applications in social network services.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.1
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• pp.39-48
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• 2012

Filtering process that separates ground and non-ground points from LIDAR data is important in order to create the digital elevation model (DEM) or extract objects on the ground. The purpose of this research is to select the most effective filtering algorithm through qualitative and quantitative analysis for the existing filtering method used to extract ground points from LIDAR data. For this, four filtering methods including Adaptive TIN(ATIN), Perspective Center-based filtering method(PC), Elevation Threshold with Expand Window(ETEW) and Progressive Morphology(PM) were applied to mountain area, urban area and the area where building and mountains exist together. Then the characteristics for each method were analyzed. For the qualitative comparison of four filtering methods used for the research, visual method was applied after creating shaded relief image. For the quantitative comparison, an absolute comparison was conducted by using control points observed by GPS and a relative comparison was conducted by the digital elevation model of the National Geographic Information Institute. Through the filtering experiment of the LIDAR data, the Adaptive TIN algorithm extracted the ground points in mountain area and urban area most effectively. In the area where buildings and mountains coexist, progressive morphology algorithm generated the best result. In addition, as a result of qualitative and quantitative comparisons, the applicable filtering algorithm regardless of topographic characteristics appeared to be ATIN algorithm.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.27 no.3
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• pp.174-178
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• 2015

This paper describes a signal processing technique for identifying signals from defects by using an electromagnetic-ultrasonic guided waves method based on a magnetostrictive sensor that generates a torsional mode (T(0, 1)). Because this technique is based on the digital filtering, the filtered signals provide information on the relationship between the cutoff frequency of band-pass filter and the characteristic of defect signals in heat exchange tubes. To verify the performance of the technique, artificial defects with various thickness reduction ration and shape were machined in titanium tubes, and digital filtering results are reported. The results show that digital filtering provides information to the identify shape of defects and the contact condition between the tube and support ring. Therefore, the proposed technique has good potential as a tool for evaluating the integrity of heat exchange tubes.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.5
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• pp.343-356
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• 1991

An efficient real-time implementation of digital filtering algorithms using a multiprocessor system in a ring network is investigated. The development time and cost for implementing a high speed signal processing system can be considerably reduced because algorithm are implemented in software using commercially available digital signal processors. This method is based on a parallel block processing approach, where a continuously supplied input data is divided into blocks, and the blocks are processed concurrently by being assigned to each processor in the system. This approach not only requires a simple interconnection network but also reduces the number of communications among the processors very much. The data dependency of the blocks to be processed concurrently brings on dependency problems between the processors in the system. A systematic scheduling method has been developed by using a processors which can be used efficiently, the methods for solving dependency problems between the processors are investigated. Implementation procedures and results for FIR, recursive (IIR), and adaptive filtering algorithms are illustrated.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.4
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• pp.13-18
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• 2012

In this paper, we propose a noise estimation method for noise reduction. It is based on block and pixel-based noise estimation. We assume that an input image is contaminated by the additive white Gaussian noise. Thus, we use an adaptive Gaussian filter and estimate the amount of noise. It computes the standard deviation of each block and estimation is performed on pixel-based operation. The proposed algorithm divides an input image into blocks. This method calculates the standard deviation of each block and finds the minimum standard deviation block. The block in flat region shows well noise and filtering effects. Blocks which have similar standard deviation are selected as test blocks. These pixels are filtered by adaptive Gaussian filtering. Then, the amount of noise is calculated by the standard deviation of the differences between noisy and filtered blocks. Experimental results show that our proposed estimation method has better results than those by existing estimation methods.

• Journal of Korea Multimedia Society
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• v.15 no.11
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• pp.1292-1304
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• 2012

Recently, digital images are extremely forged by editors or advertisers. Also, amateurs can modify images throughout easy editing programs. In this study, we propose identification and analytical methods for the modified images to figure out those problems. In modified image analysis, we classify two parts; a filtering change and a geometric change. Those changes have an algorithm based on interpolation so that we propose the algorithm which is able to analyze a trace on a modified area. With this algorithm, we implement a detection map of interpolation using minimum filter, laplacian algorithm, and maximum filter. We apply the proposed algorithm to modified image and are able to analyze its modified trace using the detection map.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.2
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• pp.151-158
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• 2004

In this paper, an inverse filtering technique for the digital filter model is proposed. This technique enables us to obtain a stable non-causal m inverse filter by transforming (approximating) it to a causal stable inverse system. In practice, a causal FIR approximation to this inverse filter is proposed. It can be shown that the impulse response of the inverse filter for all-pass systems is simply the mirror image of the impulse response for the system. Specially, due to this symmetric property of the impulse response of all-pass systems, the proposed technique is more useful for all-pass systems than other systems. In order to illustrate the proposed inverse filtering technique, four examples are presented. Two of them are for all-pass filters. The other two examples are for IIR and FIR filters. Also, computer simulations demonstrate that the proposed technique works very well.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2001.11a
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• pp.464-468
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• 2001

In this paper, we propose a robust watermarking technique that accepts time scaling, pitch shift, add noise and a lot of lossy compression such as MP3, AAC, WMA. The technique is developed based on digital filtering. Being designed according to critical band of HAS (human auditory system), the digital filters nearly affect audio quality. Furthermore, before implementing digital filtering, wavelet transform decomposes the audio signal into several signals that is composed of specific frequencies. Designed digital filters scan the decomposed signal. The designed digital filter, band-stop filter, distorts and eliminates specific frequencies of audio signals. Watermarking detection can be accomplished by FFT (Fast Fourier Transform). Firstly, segments of audio signal are transformed by FFT. Then, the obtained amplitude spectrum by FFT is summed repeatedly. Finally the watermark detector can find filters used to watermark encoding based on eliminating frequencies. The suggested technique can embed 4bits/s in a robust manner.

• Journal of Korea Multimedia Society
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• v.13 no.3
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• pp.475-486
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• 2010

Contents Recommender System predicts user's preferences towards contents, and then recommends highly-predicted contents to user. Digital Identifier plays its part in identifying abstract works or digital contents in digital network environment. Digital Identifier could be effectively used in content-based filtering and collaborative filtering that are mainly used in Contents Recommender Systems. Therefore, this paper proposes an improvement of UCI metadata and resolution service for effective use of UCI in massive contents recommender systems. UCI metadata is expanded by adding elements such as abstract, keyword, genre, age, rate and review. Resolution service allows the operation systems to collect user preference for content by including input part of preference in a result page. This paper also designs and implements an improved UCI operation system and shows that the proposed improvement of UCI metadata and resolution service could be used for massive contents recommendation.

• Journal of Digital Convergence
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• v.12 no.8
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• pp.329-335
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• 2014

Collaborative filtering has been popular in commercial recommender systems, as it successfully implements social behavior of customers by suggesting items that might fit to the interests of a user. So far, most common method to find proper items for recommendation is by searching for similar users and consulting their ratings. This paper suggests a new similarity measure for movie recommendation that is based on genre interest, instead of differences between ratings made by two users as in previous similarity measures. From extensive experiments, the proposed measure is proved to perform significantly better than classic similarity measures in terms of both prediction and recommendation qualities.